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Record W3088500871 · doi:10.1002/adem.202000777

Creped Tissue Paper: A Microarchitected Fibrous Network

2020· article· en· W3088500871 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Engineering Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMicroscale chemistryComposite materialMicrostructureBendingDeformation (meteorology)FiberUltimate tensile strengthBuckling

Abstract

fetched live from OpenAlex

Tissue paper is a thin complex nonlinear fibrous material made from fiber layers thinner (≈100 μm) than a human hair. Though it appears as a slender two‐dimensional material to our eyes, its internal microstructure reveals an intricate architected fibrous network of only 1–5 wood fibers within its thickness. The fiber network is folded in one direction giving rise to a characteristic crepe structure. Using high‐speed imaging, the crepe structure is shown to emerge from a dynamic, coupled mechanical deformation processes of fracture and buckling, occurring on a length scale of few hundred micrometer. Bending and stretching of the folds at the macroscale of the paper and at the microscale of the individual fibers are shown to govern the material's tensile properties, including the strain to rupture and the elastic modulus. Insights from this study can guide the development of strong, soft fibrous materials for biomedical and consumer products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.173
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it